基于BP神经网络的救援机械臂的逆运动学求解

    Inverse Kinematics Solution of Rescue Robotic Arm Based on BP Neural Network

    • 摘要: 针对灾害救援的复杂性、危险性,提出一种高负载自重比的救援机械臂构型,建立三维模型,通过Denavit-Hartenberg方法对五自由度机械臂建立正逆运动学模型,利用MATLAB机器人工具箱构建救援机械臂的仿真模型,验证运动学模型的正确性,采用10输入、5输出、3层的BP神经网络进行逆运动学解的预测,对用解析法得到的4组运动学逆解进行筛选,从而得到唯一的精确逆解,为后续机械臂的轨迹规划的实现奠定了基础.

       

      Abstract: To solve the problem of the complexity and danger of natural disaster rescue, a rescue robotic arm with high load to weight ratio was proposed, and a three-dimensional model was established. The forward and inverse kinematics models of the multi-degree-of-freedom mechanical arm were established through the Denavit-Hartenberg method, and the simulation model of the rescue robotic arm was established by using the MATLAB robot toolbox to verify the correctness of the forward and inverse kinematics models. A 10-input, 5-output, 3-layer BP neural network was used to predict the inverse kinematics, and the 4 group kinematics inverse solution was screened to obtain the only accurate inverse solution, which lays a foundation for the realization of the subsequent trajectory planning of the robotic arm.

       

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